How Amazon And Other Retailers' Supply Chains Will Boost Use Cases For Autonomous Trucks

Imagine this: you’re driving on the road right behind a convoy of trucks moving together fluidly like a highly synchronized chorus line. There are no glittering sequins and feathered headdresses though. Instead, there are drivers kitted out in electrode studded caps and enormous glasses. If you are particularly observant, you might also notice that it’s only the lead driver who actually seems to be driving. Then again, you don’t really need to imagine all this because real-world trials of platooning—a line of semi-autonomous trucks able to cover reasonable distances—have already begun.

This represents just one of the many ways in which autonomous trucks will disrupt the business models and logistics supply chains of retailers, including striking the possible death knell of traditional warehouses. It will also mean a (welcome) change for customers since such autonomous technologies will enable online retail giants like Amazon and Alibaba to address long standing challenges in long haul and last mile deliveries.

Autonomous Technologies To Disrupt Logistics And Supply Chain Models

At the most basic level, autonomous trucks will support better productivity, efficiency and flexibility in the transport and logistics sector, as well as in industries that depend on trucking. This is for the simple reason that technologies, like truck drivers, might have names like Alexa, Siri and, yes, well, Vera (Volvo’s latest concept for an autonomous electric truck) but unlike their human counterparts, can work continuously without being hemmed in by either labor laws or collapsing from fatigue. (How about naming the next autonomous truck after that tireless striver, Hercules?) This would mean an optimal flow of goods…manna for consumers since it would mean much faster delivery times.

Backed by these prospective benefits, and if all goes according to plan, the scope for use of autonomous trucks will widen. From being deployed in airports, ports, construction areas and warehouses, to being used for hub-to-hub transfers, transitioning from there to intrastate and interstate long haul applications, and, from there, on to hub-to-dock and dock-to-dock transfers at a regional level, autonomous trucks will transform the entire logistics ecosystem.

I see three areas—hub-to-hub long transit, inner city delivery, and first and last mile delivery—where autonomous trucking will most clearly disrupt current logistics and supply chain models.

Hub-to-hub Long Transit Makes Strides

Current supply chains are based on a traditional hub-and-spoke model. Autonomous trucking will create transitional disruption to this logistics model, with special use cases for L2 and L4 trucking that will introduce new nodes in the model.

Emergence of transfer hubs to connect highways and destinations: Earlier this year, Waymo announced that its autonomous trucks would soon start transporting freight for Google’s data centers in Atlanta. Meanwhile, Uber’s autonomous trucks use a transfer hub model—a combination of autonomous driving on the highway and drivers for the last stretch—to make deliveries in Arizona.

Inter-fleet communication: In current hub-to-hub platooning trials, the average gap between trucks is 50 meters. This poses challenges in complex intersections and highway driving scenarios. L4 automation aims to reduce this gap to 10-25 meters, with braking time reduced from 1.5 seconds to 0.03 seconds, thereby enabling true hub-to-hub automated driving solutions.

I expect the early L4 trucking applications to come to market by 2021 with use cases in hub-to-hub, intrastate highways, and trailer switching at hubs.

Early indications in technology and cost benefit analysis reveal that L4 truck platooning will soon pave the way for L4 autonomous trucking as it addresses challenges in traffic, transport and transshipment.

Traffic: Difficulties with auto emergency braking (AEB) and latency in virtual-to-virtual (V2V) technologies affect traffic efficiency in terms of vehicle gap and number of trucks in the platoon. HD mapping and sensors will help L4 trucks tackle these two problem areas and overcome challenges related to keeping a minimum distance between trucks and intersection automation.

Transport: Currently, there are significant delays in inventory transfers from hubs to various docks within city limits. L4 autonomous trucks and inventory planning will support greater flexibility and higher efficiency of goods transfer in dock-to-dock and dock-to-hub applications. This will reduce the payback time for L4 technology investment.

Applications in dock-to-dock and interstate/country highways logistics will mark the second wave of L4 trucking, and will most likely take off around 2028. The same body and cabin will be used for HD and MD trucks, especially in electric mode, enabling greater flexibility in how, where and for what the vehicle is used.

Transshipment: The efficiency of trucks reduces considerably once they enter a transshipment port as there is often a delay in reaching various goods in a truck to the right dock. However, features like automated docking, inter-terminal movement of automated cabins and pre-planned routing of containers, can significantly improve the terminal’s efficiency.

New Inner City Delivery Models To Drive Opportunities In MD Trucks

I see a very strong possibility of automation being introduced in the MD trucking space, with the highest potential for automation in the 8-12 ton trucks for inner city delivery models, primarily in retail. Synergies between these two sectors will grow due to the increasing digitization of their respective value chains.

In retail, the emergence of new supply chain models, like commingling and split inventory, will disrupt current norms and pave the way for automation within inner city limits. Let me explain how these two models work.

In the commingling model, a product is purchased from vendor A but the location of delivery is closer to a warehouse of vendor B. So vendor A requests vendor B to deliver the product and schedules an autonomous delivery of the product to the warehouse of vendor B, along with a small share of the profit margin. This will meet the demand for faster delivery times and will also help improve logistics utilization.

Split inventory is another emerging trend. Based on the demand for certain goods, centralized warehouses split the availability of goods to smaller warehouses in order to make shorter delivery times. Once the localized dock is established, delivery can be achieved using innovative first and last mile delivery methods.

First And Last Mile Delivery To Sync With Amazon And Other Retailers’ Needs

Frost & Sullivan

Today 7% to 20% (depending upon cities and e-commerce trends) of urban traffic comprises delivery vehicles but contributes to 20% to 35% of urban congestion. The lack of proximate parking and the intensifying pressures of same day or even 2-hour delivery expectations have caused stark imbalances in logistics delivery models, particularly in urban areas. Current ‘stop & walk’ delivery models— where trucks are driven about 1-2 miles from one urban parking bay to another, with the driver then walking to make the final door delivery service—are highly inefficient. They result in a nearly 15 to 20% underutilization of the delivery time per driver, and a reduction in the area covered by the delivery vehicle.

This is spurring developments of mobile hub-and-spoke solutions coming into a telescopic logistics model. With this, we will see the introduction of shorter, automated logistics delivery models that connect spokes/docks to improved access points. From here, mobile delivery hubs will provide faster access to the goods, which can then be reached to their final destinations, either in person or by drones or pods. This new model will, thereby, improve utilization rates and range per hub.